First report of rapid, non-invasive, and reagent-free detection of malaria through the skin of patients with a beam of infrared light

Abstract

We describe the first application of the Near-infrared spectroscopy (NIRS) technique to detect Plasmodium falciparum and P. vivax malaria parasites through the skin of malaria positive and negative human subjects. NIRS is a rapid, non-invasive and reagent free technique which involves rapid interaction of a beam of light with a biological sample to produce diagnostic signatures in seconds. We used a handheld, miniaturized spectrometer to shine NIRS light on the ear, arm and finger of P. falciparum (n=7) and P. vivax (n=20) positive people and malaria negative individuals (n=33) in a malaria endemic setting in Brazil. Supervised machine learning algorithms for predicting the presence or absence of malaria were applied to predict malaria infection status in independent individuals (n=12). Separate machine learning algorithms for differentiating P. falciparum from P. vivax infected subjects were developed using spectra from the arm and ear of P. falciparum and P. vivax (n=108) and the resultant model predicted infection in spectra of their fingers (n=54). NIRS non-invasively detected malaria positive and negative individuals that were excluded from the model with 100% sensitivity, 83% specificity and 92% accuracy (n=12) with spectra collected from the arm. Moreover, NIRS also correctly differentiated P. vivax from P. falciparum positive individuals with a predictive accuracy of 93% (n=54). These findings are promising but further work on a larger scale is needed to address several gaps in knowledge and establish the full capacity of NIRS as a non-invasive diagnostic tool for malaria. It is recommended that the tool is further evaluated in multiple epidemiological and demographic settings where other factors such as age, mixed infection and skin colour can be incorporated into predictive algorithms to produce more robust models for universal diagnosis of malaria.

Identification of visible and near-infrared signature peaks for arboviruses andPlasmodium

“…If further assessed these arboviruses and P. falciparium could be developed into biomarkers of these pathogens in human samples. NIRS is an easy to use, rapid, potable, and reagent free technique [67, 75–77]. Once machine learning techniques are developed, the feasibility for on-site largescale diagnosis of patients is feasible.…”

“…If further assessed these arboviruses and P. falciparium could be developed into biomarkers of these pathogens in human samples. NIRS is an easy to use, rapid, potable, and reagent free technique [67,[75][76][77].…”

Malaria therapeutics: are we close enough?

“…The study in Brazil showed 92% accuracy for the arm and 93% predictive accuracy for differentiating between P. falciparum and P. vivax . The bands observed in the spectra enable the identification of positive and negative malaria cases and are mainly due to hemozoin [ 208 ].

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